Get Smart: The Value of Fully Integrated Sample Preparation for Chromatography/Mass Spectrometry

• University of Geneva
• University of Lausanne
• CTC Analytics AG

Abstract

Using a case study in metabolomics, undertaken on a robotic sample prep platform, we will present results that show how fully integrated ‘smart’ automation produces better quality samples and significantly improves the accuracy and repeatability of an analysis, whilst streamlining workflow.

Introduction

Pharmaceutical companies are under increasing pressure to bring products from discovery through to market quickly and cost-effectively. Where this isn’t possible, ‘fail early, fail cheap’ have become industry watchwords in a sector where commercial drivers dictate that investment is focused where products can be most readily developed. Consequently, maximizing the value of analytical techniques which inform the drug discovery and development pipeline – as well as subsequent manufacturing processes - is an important strategy.

Chromatography, especially when combined with mass spectrometry, is one of the most commonly used analytical techniques due to its high sensitivity, specificity and precision¹. It plays a crucial role in the early stages of drug development when information about the impurities and degradation of products in a drug substance and/or drug product is inadequate. Data obtained by chromatography analysis has long been used to support regulatory applications. Chromatography systems have become increasingly sophisticated, and a number of high performance techniques have emerged along with hyphenated systems, which have been widely adopted in the pharmaceutical industry for drug analysis.

The Challenges of Successful Sample Preparation

The time pressures faced by drug developers to bring products to market compress research and development time-frames, and impact laboratory analysis too. One consequence has been the introduction of automation of all kinds within the laboratory to accelerate workflows. With technological development, there have been huge advances in lab automation over the past decade. Now, as the importance of chromatography data to inform the drug approvals process increases, further automation is being encouraged in this area, for example, as the technique moves into the high throughput environment, particularly in the areas of antibody purification and proteomics.

Despite the fact that many instrumental chromatographic techniques have matured and automation of some kind is commonplace, sample preparation remains a bottleneck in laboratory processes. A recent publication² established that 60% of chromatography analysts believe the biggest challenge in sample preparation is the time and labor intensity of the procedure.

It is also widely accepted that sample collection, preparation and processing is by far the largest source of error in analytical laboratories³. It is a multifactorial process presenting many opportunities for error to occur during sample collection and storage, preparation chemistry and extraction, or indeed at any number of the multiple steps prior to separation and analysis.

Introducing Smart Automation

When automating sample preparation many scientists adopt two separate options: robotic sample preparation or automated sample injection. Whilst there are advantages to automating these two processes in isolation, the entire sample preparation workflow still includes numerous manual steps, most notably in the need to transfer of samples from one system to another.

However, with the emergence of fully integrated automated systems, which combine sample preparation (e.g. standard addition, liquid/liquid extraction, SPE) and injection on a single platform, this intermediate step can be eliminated. Automating the entire preparation process in this way can significantly decrease sample preparation time and error rate. Able to run 24/7 without human intervention, ‘smart’ automated systems are also proven to increase productivity and facilitate high sample throughput, allowing scientists to focus on the skilled analysis and interpretation of the results rather than on time-consuming wet chemistry.

Case Study: Bligh & Dyer Automation

In this metabolomics study on algae cell cultures, a PAL RTC platform as seen in Figure 1 was used to complete the necessary Bligh and Dyer sample preparation protocol (liquid/liquid extraction) and manage sample injection. Utilizing this set-up, a fully automated protocol has been developed, which combines Bligh and Dyer extraction with dualcolumn UHPLC-MS/MS separation for the metabolic analysis of algae cell culture.

 Figure 1. Annotated image of robotic sample prep platform

 Figure 2. Preliminary steps - offline

he necessary sample preparation steps. This included adding the set reagents and splitting the aqueous and organic fractions prior to injection into the LC (Figure 3). Even with the initial manual step, this automated method proved significantly less laborintensive than the conventional manual method, and significantly reduced the overall sample preparation time.

Table 1 lists the different metabolites from the algae cells identified by the analyses of the upper (aqueous) and lower (organic) fractions. Only a few compounds with ampiphilic properties (pka-values were calculated), such as metoprolol, were retrieved in both upper and lower fractions. These results are in agreement with comparative analyses of manually extracted samples. Analytical results obtained using a robotic sample prep platform can be directly subjected to a library search using LC-MS/MS data in SWATH mode, eliminating the need for further targeted experiments to identify unknowns. This significantly reduced experimental time and resulted in faster processing of results.

 Figure 3. Automated on-line sample preparation

Table 1. Calculated logP, logD and pKa for the compounds analyzed

Manual sample preparations were performed in parallel to assess the repeatability of this automated Bligh and Dyer extraction, which also allowed for comparison of any variation between the two methods. As is shown in Figure 4, the automated method had lower variation and, therefore, better repeatability for both the aqueous and organic fractions. This is particularly noticeable for the aqueous fraction at pH 8.3 and the organic fractions.

 Figure 4.Column diagrams showing the peak areas of selected variables (by m/z and retention time, RT) as well as variation obtained after analysis of the aqueous (AQ) and organic (ORG) B&D fractions from the automated or the manual extraction proce¬dure (n=5): a) AQ fractions at pH 3 - C18 column, b) AQ fractions at pH 8 - C18 column, c) ORG fractions (pH 4) - C8 column.

Conclusion

Optimizing the value of analytical techniques to better inform the early stages of drug discovery and development is an important strategy for the pharmaceutical community. Advances in analytical instruments are improving data quality, robustness and speed of delivery to researchers. Simultaneously, the emergence of automated systems is increasing accuracy and productivity in the laboratory setting, helping an industry to meet the combined challenges of growing market demand, economic pressures and evolving regulatory guidance.

Fully integrated automation of the sample preparation process paves the way for improved test accuracy and reproducibility, better quality data and increased laboratory productivity. Such an approach has an important role to play in bringing new pharmaceutical products to market in a timely and efficient manner.

References

1. S Jensen. Lipid Technology 2008, 20: 288-81 doi:>>10.1002/lite.200800074
2. http://www.chromatographyonline.com/trends-sample-preparation-3
3. Sample preparation fundamentals for chromatography, Agilent Technologies, publication no 5991-3326EN